Function Points

Test Your Knowledge

Function Points Quiz

Instructions: Choose the best answer for each question.

1. What is the primary advantage of using Function Points over Lines of Code (LOC) for software sizing?

a) Function Points are easier to calculate. b) Function Points consider only the physical code size. c) Function Points measure the functional complexity of the system. d) Function Points are more suitable for small-scale projects.

2. Which of the following is NOT a component of Function Point analysis?

a) External Inputs (EI) b) External Outputs (EO) c) Internal Data Structures (IDS) d) External Interface Files (EIF)

3. What is the main purpose of determining the complexity of each Function Point component?

a) To simplify the calculation process. b) To identify potential design flaws. c) To accurately reflect the effort required for implementation. d) To compare the size of different software systems.

4. Which of the following is NOT a benefit of using Function Points for software estimation?

a) Improved communication between stakeholders. b) Accurate cost estimation and resource allocation. c) Easier project management for waterfall methodologies. d) Objective comparison of software project sizes.

5. What is the final step in the Function Point analysis process?

a) Identifying functional components. b) Classifying components based on their type. c) Determining complexity of each component. d) Calculating the total Function Points using predefined formulas.

Function Points Exercise

Scenario:

You are tasked with estimating the size of a new online banking application using Function Points. The application has the following features:

• Customer login: Users can log in with their username and password.
• Account balance inquiry: Users can view their account balances.
• Transaction history: Users can view a detailed history of their transactions.
• Transfer funds: Users can transfer funds between their own accounts.
• Bill payment: Users can pay bills directly from their accounts.

Instructions:

1. Identify the functional components of the application and categorize them based on the five Function Point elements (EI, EO, EQ, ILF, EIF).
2. Determine a complexity rating for each component (simple, average, complex).
3. Calculate the total Function Points based on the complexity and component count.

Techniques

Function Points: A Deep Dive

Chapter 1: Techniques

Function Point Analysis (FPA) employs several techniques to accurately measure software functionality. The core technique is the identification and quantification of the five functional components: External Inputs (EI), External Outputs (EO), External Inquiries (EQ), Internal Logical Files (ILF), and External Interface Files (EIF). These are then weighted based on their complexity. The complexity weighting considers factors such as:

• Data elements: The number of data elements involved in the function.
• Data structures: The complexity of the data structures used.
• Processing logic: The complexity of the algorithms and calculations performed.
• Control flow: The complexity of the program's control flow.

Different FPA methods exist, varying slightly in their complexity weighting and calculation formulas. The most common are:

• Mark II: A widely adopted standard, offering a relatively straightforward approach.
• ISO/IEC 14143-1: An international standard providing a more rigorous and detailed framework.

These techniques ensure a systematic approach, reducing subjectivity and improving the consistency of measurements across different projects and teams. Beyond the basic counting, expert judgment plays a vital role in assigning complexity weights, accurately reflecting the true functional complexity.

Chapter 2: Models

Several models underpin Function Point analysis, all striving to capture the essence of software functionality beyond mere lines of code. The core model is based on the five functional components mentioned earlier (EI, EO, EQ, ILF, EIF). These components represent different aspects of user interaction and data management within the system.

The complexity adjustment is a crucial aspect of the model, moving beyond simple counting. It recognizes that functions can vary significantly in complexity, and this variation significantly impacts development effort. The weighting schemes used (e.g., simple, average, complex) within the various FPA standards (like Mark II and ISO/IEC 14143-1) reflect different approaches to this complexity assessment. These models often involve detailed tables and scoring mechanisms to ensure consistency and objectivity in the assignment of complexity weights.

Some advanced models integrate FPA with other estimation techniques, such as use case points or object points, providing a more holistic and comprehensive view of software size and complexity.

Chapter 3: Software

While FPA is a manual process at its core, software tools significantly improve efficiency and accuracy. These tools automate the tedious task of counting function components and applying complexity weights, reducing the risk of human error.

Key features of FPA software include:

• Automated counting: The software automatically counts the number of each function component based on user input.
• Complexity weighting: The software assists in assigning complexity weights to each component, often providing guidance and suggestions based on defined rules.
• Function Point calculation: The software automatically calculates the total Function Points based on the chosen method and complexity weights.
• Reporting and analysis: The software generates reports summarizing the FPA results, including detailed breakdowns of function components and complexity weights.
• Data import/export: Some tools offer features to import data from other project management systems or export data for further analysis.

Examples of such software include commercial tools, open-source projects, and even spreadsheets with custom formulas. The choice of software depends on project needs, budget, and organizational preferences.

Chapter 4: Best Practices

Effective use of Function Points requires adherence to best practices:

• Consistent definitions: Ensure clear and consistent definitions for each of the five functional components across the project team. Ambiguity can lead to inaccuracies.
• Team training: Provide thorough training to all team members involved in the FPA process to ensure everyone understands the methodology and applies it consistently.
• Regular review: Regularly review and validate the FPA results to identify and correct any errors or inconsistencies.
• Use of standard methodologies: Follow a recognized standard like Mark II or ISO/IEC 14143-1 to maintain consistency and comparability across projects.
• Early involvement: Involve the FPA process early in the project lifecycle to ensure that the requirements are well-defined and understood.
• Iterative approach: Employ an iterative approach, refining the FPA estimates as the project progresses and the requirements evolve.
• Calibration: Regularly calibrate the FPA process against actual development effort to refine the accuracy of the estimation models.

Chapter 5: Case Studies

Case studies demonstrate the practical application of Function Points across diverse software projects. Examples include:

• Case Study 1: A Banking System: FPA successfully estimated the development effort for a new online banking system, leading to accurate budgeting and resource allocation. This involved a detailed breakdown of the system's various functionalities, including user accounts, transaction processing, and reporting.
• Case Study 2: An E-commerce Platform: Function Points helped a team accurately size and estimate a large-scale e-commerce platform, facilitating better project planning and risk management. This highlighted the ability of FPA to handle complex systems with numerous interactions.
• Case Study 3: A Mobile Application: A mobile application development project utilized FPA to estimate the effort required for each feature, enabling agile development and iterative refinement.

These case studies illustrate how FPA provides a more robust and reliable approach to software sizing and estimation compared to simpler methods like lines of code, leading to better project management and control. They emphasize the importance of careful planning and the iterative nature of FPA in real-world scenarios.